This computational research project will analyze gastrointestinal microbiome, host cellular immune response, and host transcriptional response datasets derived from a large-scale rhesus macaque AIDS vaccine study. The vaccine study includes 70 animals divided into five groups and is designed to test the efficacy of a cytomegalovirus (CMV) vector expressing the major simian immunodeficiency virus (SIV) proteins. In previous studies, RhCMV/SIV vaccines elicit a robust effector-memory T cell response. After challenge with highly pathogenic SIVmac239, approximately 50% of RhCMV/SIV-vaccinated monkeys exhibit a pattern of viral control that is characterized by a blip of viremia followed by control of plasma viremia to undetectable levels. One to three years later, RhCMV/SIV-protected monkeys show no sign of SIV infection, suggesting immune-mediated clearance of the virus. The mechanisms responsible for this 50% efficacy are not clear, but may reflect T cell responses at the site of SIV entry or sites of early replication. Thi project will investigate the role of the gastrointestinal microbiome on RhCMV/SIV-induced effector-memory T cell responses and protection against SIVmac239 challenge. The project includes two computationally based Specific Aims: 1) Define the composition of the gut microbiome prior to and after vaccination and during repeated limiting-dose SIVmac239 challenge; and 2) Determine how the composition of the gut microbiome correlates with protective immune cell responses and vaccine-induced host transcriptional responses. In Aim 1, 16S ribosomal sequence data (obtained from rectal swabs) will be used to determine operational taxonomic units. Variation in bacterial species over time and within individual animals will be determined using Mothur and Qiime metagenomic software. Nonparametric statistical analyses and co-occurrence and co-exclusion networks will be used to identify bacterial species associated with progression or control of SIV infection after repeated limiting-dose intrarectal SIVmac239 challenge. In Aim 2, principle component analysis will be used to identify associations between microbiome composition and SIV-specific CD4+ and CD8+ T cell responses. Gene module-based and correlation network-based approaches will be used to determine associations between microbiome composition and host transcriptional responses (collected from whole blood samples). Together, these analyses will allow us to better understand microbiome-host interactions and their role in eliciting a protective vaccine-derived effector-memory T cell response. Such understanding will inform future vaccination strategies and attempts to modulate microbiome composition to affect vaccine efficacy.